Lecture
1: Course Overview and Review of Institutions and Markets
The goals of this class
- Understand important financial institutions and markets
- Provide a toolkit for creating portfolios of financial assets
- Use asset pricing models to understand the
trade-off between risk and return
- Apply these models to:
- identify investment opportunities
- evaluate portfolio performance
Who am I?
- Former research economist at the Federal Reserve Bank of New York
(2015-2018)
- PhD in economics at Harvard from 2009-2015
- Research associate at the FRBNY (2007-2009)
- Main research focus:
- Consumer finance – bankruptcy,
mortgages, housing
- Applied statistics – machine
learning and other methods
- Email: paul.goldsmith-pinkham@yale.edu
- Please reach out if you have any concerns or questions re: policy
that are not laid out in the syllabus.
- Website: http://paulgp.github.io
Timeline for our course
Part 1:
Institutional details + setting the stage
What we’ll learn:
- Who are the buyers and issuers of financial instruments?
- Define assets + securities classes
- How are financial assets traded?
- How have these financial assets performed historically?
- Strong focus on statistical properties and data
Questions to consider:
- Why do people + institutions trade assets?
- Why do investments make money?
- What is the goal of investments?
Timeline for our course
What we’ll learn
- How do we interpret observed returns?
- Build to a model of returns
- Three ingredients necessary for our models:
- Defining risk appetite/aversion
- Understanding mean‐variance trade-off
- Allocating between risky and safe investments
- Use models to construct a portfolio of risky investments
- Capital Asset
Pricing Model
- Arbitrage Pricing
Theory / Factor Models
Questions to consider:
- What is the goal of an investment portfolio?
- What is risk? How do I quantify it (vs. return)?
- What simplifications am I willing to assume?
Timeline for our course
What we’ll learn
- How consistent is CAPM with the data?
- How consistent is the data with APT?
- Markets are efficient? Or is it behavioral?
- How should we use the models when there are market anomalies?
- Active portfolio management
- Treynor-Black / Black-Litterman
- Robust Portfolio Management
Questions to consider:
- Are my portfolio decisions intuitive?
- What am I missing?
Timeline for our course
Part 4:
Evaluate and attribute portfolio returns
What we’ll learn
- CAPM / APT describe returns from a passive strategy (no
skill required)
- How should we evaluate active managers?
- Portfolio evaluation techniques answers:
“Did you beat your benchmark?”
- Performance attribution answers the question,
“How did you beat your benchmark?”
Timeline for our course
What are other investment
settings?
- Private equity and hedge funds
- International investing
- Fixed income (bonds)
- Derivatives (options, forwards, futures)
Key focus:
- What changes when you shift markets?
Class requirements
- Straight from the syllabus!
- Two problem sets as homework:
- Due February 17 and March 7
- To be done individually
- One case write-ups:
- Yale University Investments Office (Due in class April 4)
- To be done in groups 3-5
- New this year:
- Final exam
- No midterm
- Every class will have a short multiple-choice quiz to test your
understanding of the material (also to encourage attendance)
TA: Wesley Wong
Understand the marketplace
Know thy enemy and know yourself; in a hundred battles, you will
never be defeated. When you are ignorant of the enemy but know yourself,
your chances of winning or losing are equal. If ignorant both of your
enemy and of yourself, you are sure to be defeated in every battle.
- Who are the participants in the equity market?
- Overall estimated level AuM (globally) as of 2022: 115+ trillion
dollars (more than global GDP).
- What institutions hold most assets under management (AUM)?
- What incentives do they have?
Institutions
Global assets under
management
Institutions
U.S. Institutional Holdings

Institutions
Mutual Funds
- Also known as open-end funds
- Investors pool and benefit from sharing information
collection
and back‐office costs
- Fund issues new shares when investors buy in and redeems shares when
investors cash out
- Priced at Net Asset Value (NAV):
\[ \frac{\text{Market Value of Assets} -
\text{Liabilities}}{\text{Shares Outstanding}} \]
Institutions
Mutual Funds Fees
- Fee Structure: Four types
- Operating expenses (recurring)
- 12 b‐1 charge (recurring)
- Front‐end load (one time)
- Back‐end load (one time)
- Fees must be disclosed in the prospectus
- Share classes with different fee combinations
Institutions
Example of
fees for various classes of mutual funds
- Compare the A, B and C shares
- What are the trade-offs between initial and deferred loads?
- Level of annual fees and expenses
Mutual Funds - fees and
incentives
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Mutual Funds - fees and
incentives
Fund flow response distorts risk-taking incentives (Chevalier and
Ellison (1997))
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Mutual Funds - costs over
time
Mutual fund expense ratios have fallen over time, driven by several
factors
- Scale economies - assets under management have grown
- Competition - investors pick funds with lower expense ratios
- Increased presence of employer-sponsored retirement plans

Do mutual fund managers
earn their fees?
- How could we answer this?
- One idea: how do mutual funds do compared to an index?
- Performance of actively managed funds below the return on:
- the Wilshire index in 23 of the 39 years from 1971 to 2009
- the S&P index in 30 of the 47 years from 1970 to 2017

Matt Levine Reading
- “Active investment funds should be illegal for fiduciaries.” Do you
agree or disagree?
Institutions
Mutual Funds -
do fund managers earn their fees?
- Are all mutual fund managers like Andy Dwyer, or just the
average?
- Malkiel (1995) evaluates 239 mutual funds with at least ten-year
records
- Compare each fund’s performance to holding the S&P 500
Institutions
Is there a “hot
hand” for mutual fund managers?
- Evidence for persistent performance is weak, but suggestive
- Malkiel (1995) tracks funds based on above/below median
performance:

Institutions
- Bollen and Busse (2004) find tiny persistence at the quarterly
level

Institutions
Mutual Funds – luck or skill?
Fama French “Luck vs Skill in Mutual Fund Returns” 2010
- Value weighted portfolio of active funds earns the market return,
minus fees
- Distribution of “alpha” looks more consistent with luck than
skill
Net Returns

Institutions
Mutual Funds – luck or skill?
Fama French “Luck vs Skill in Mutual Fund Returns” 2010
- Value weighted portfolio of active funds earns the market return,
minus fees
- Distribution of “alpha” looks more consistent with luck than
skill
Gross Returns

Institutions
Closed-End Funds
- Unlike mutual funds (open-end), no change in shares outstanding
- Old investors cash out by selling to new investors
- Managers unburdened with managing flows
- Traded continuously on exchanges
- Priced at premium or discount to NAV
- No easy arbitrage to close price gaps
- Hedge funds may ride discounts
- Alternatively, may attempt to “open” funds
Institutions
What else? Other
buyers/Other perspectives
- Pension funds
- Endowment Funds
- Alternative Asset Managers
- to be discussed in the context of cases and guest lectures
- Next up…market structure
Market Structure
What kinds of markets are
there?
- Specialist Markets
- Over-the-counter (OTC) markets
- Electronic Communication Markets
Market Structure
What types of orders are
there?
- Market order – Buy or sell order to be executed immediately at
prevailing bid/ask price
- Limit order – Buy or sell order with a pre‐specified limit for the
price
- Stop order
- Buy or sell order at the market price if specified threshold is
crossed
Limit orders make up a
limit order book
Limit orders make up
a limit order book
Market Structure
Types of Markets:
Specialist Exchanges
- Example of a specialist exchange: NYSE
- Trading traditionally occurred through a combination of an auction
(the order book) and a market maker (the specialist)
- Orders sent to exchange may be cleared electronically or sent to
specialist
- Only one specialist for each stock
- Specialist may act as broker or as a dealer
Market Structure
Roles of
specialists in specialist exchanges
- Broker
- Matches buy and sell orders
- Income generated by commissions
- Dealer
- Specialists maintain their own bid and ask quotes and fill orders
with own account if market spread too high
- Historically, participated in about 25% of all transactions
- Maintained price continuity
Market Structure
Types of Markets: OTC Markets
- Trades negotiated dealer‐to‐dealer
- Nasdaq (National Association of Securities Dealers Automated
Quotation system)
- Originally, a price quotation system
- Large orders may still be negotiated through brokers and
dealers
- Today, NASDAQ provides electronic trading (less OTC)
Market Structure
Types of
Markets: Electronic Communication Networks
- Private computer networks that directly link buyers with sellers for
automated order execution
- To attract liquidity, networks may pay rebates to liquidity
providers (market makers)
- Electronic clearing facilitates high frequency trading
Market Structure
Electronic
Communication Networks and high-frequency trading
- Risks of high speed algorithmic trading include market
disruption
- Flash Crash (2010)
- On May 6, 2010, US indices fell by more than 5% in a matter of
minutes, before rebounding almost as quickly
- Knight Capital (2012)
- Flawed deployment of new trading program bankrupts major market
maker
- Lost 440 million dollars from one programming mistake
Market Structure
Electronic
Communication Networks and flash crashes
SEC findings suggest the decline was triggered by a large automated
sell order for S&P futures by a mutual fund
- Existing low volume due to high market uncertainty
- Sell order (75K contracts) was an automated algorithm that directed
to sell 9% of prior minute’s trading volume
- HFTs responded to high volume of trades, but could not find
fundamental buyers (SEC describes a game of “hot‐ potato”)
- High volume led to acceleration in sell order speed, which drove
higher volatility and volume
Market Structure
Short-selling
- In our optimal portfolio, we’ll have the option to “short”–sell
stocks that we don’t own
- Why would we?
- Stock may be overpriced (negative alpha)
- Stock may be appropriately priced, but we want to hedge out risk
from a long position in a similar security (pairs trading)
- So what is it?
Market Structure
Short-selling Mechanics
Suppose we have one dollar and believe stock A will underperform
stock B.
- Buy $1 of asset B
- Borrow $1 worth of stock A ( \(1 \big/
P_A\) shares) and promptly sell the stock
- Now, you owe the owner of A his shares back and will have to
repurchase them in the market at tomorrow’s price
- Proceeds from the sale serve as collateral to stock lender
(e.g. $1)
- Reg T requires 50% additional collateral (above and beyond proceeds)
be kept in account (shares of B will suffice)
\[\text{Final Payoff} = 1 + (r_B ‐
r_A) + \ldots+ \underbrace{\text{short rebate}}_{\text{to be
defined}}\]
Market Structure
Short-selling Mechanics
Assume that \(P_{A} = 100\), and
you want to short the stock. What will your return be if the stock drops
to \(P_{A} = 25\)?
First, calculate your initial position:
- You will borrow a share of stock A and sell it immediately. You now
have $100 dollars, but owe 1 share of Stock A.
- You addditionally post the required 50% collateral (e.g. $50 of a
treasury bill)
| Cash 100 |
Short position 100 |
| T-Bill Collateral 50 |
Equity 50 |
- Now imagine the stock drops to \(P_{A}\) = 25 and you close your position:
- You buy the stock at $25, and return it to the original owner
- The collateral and cash are returned to you, net of your
purchase
- As a result, you have 75 dollars profit. Your return is \(r_{\text{short}} = \frac{75}{100} =
0.75\)
- Note that the maximum upside is a return of 100%. Why? Because the
initial sale at 100$ creates a liability of $100 dollars – at best, this
liability goes to zero, netting 100 dollars in profit and a return of
100%.
- Note that the downside is unlimited.
Market Structure
Short-selling Mechanics
Now assume we do this in pairs. There are two stocks, \(A\) and \(B\), each worth 100 dollars.We buy stock
\(B\) and short stock \(A\). What will your return be if next
period, \(P_{A} = 90\) and \(P_{B} = 105\)?
First, calculate your initial position:
- You will borrow a share of stock A and sell it immediately. You now
have $100 dollars, but owe 1 share of Stock A.
- You addditionally post the required 50% collateral (you can post
stock \(B\) shares)
| Cash 100 |
Short position 100 |
| Stock B Collateral 50 |
Equity 100 |
| Stock B 50 |
|
- Now imagine the stocks change to \(P_{A} =
90\) and \(P_{B} = 105\) and you
close your position:
- You buy the stock at $90, and return it to the original owner
- The collateral and cash are returned to you, net of your
purchase
- You sell Stock B at $105
- As a result, you have 10 dollars profit from stock A and 5 dollars
profit from stock B.
- Your returns are \(r_{\text{short}} =
-r_{A} = 0.1\) and \(r_{\text{long}} =
r_{B}\) = 0.05
- Our total profit is 15 dollars. Our net return is ((100 - 90) + (105
- 100))/100 =0.15.
Market Structure
What is the short rebate?
- Short rebate is the interest I earn on my dollar of collateral
sitting with the stock lender
\[ \text{Short Rebate} = r_{f} -
\text{Security lending Fee} \]
- Securities lending fees vary greatly and reflect how easy the shares
are to borrow (often less than 20 bps)
- In obvious shorting situations, short rebate will go negative
(shares “hot or trading “special”) or can’t be found
The peculiar case of GameStop and r/WallStreetBets
Before moving into our example, a quick poll.
Were you aware of Gamestop’s unusual stock market activity in
2021?
Did you buy either Gamestop or AMC or any related
“stonks”?
The peculiar case of GameStop and r/WallStreetBets
GameStop is a videogame retail company with poor outlook
pre-pandemic, and little strategy for the pandemic
- potential for a “turnaround” with new board members, etc. but
unlikely
Shorting this stock is a natural strategy
However, coordinated stock purchasing (a short squeeze) can make
this untenable
- Why? Short covering creates a feedback loop
Market Structure
Alternative
ways to short stocks: synthetic shorts
Consider the following replicating strategy:
- Buy a put and sell a call at the current strike price
- Have the option to sell stock at current price (put option)
- Give someone else the option to buy the stock at today’s price (call
option)
- What happens if real stock goes down 10x? up 10x?
- However, options traded on less than half of publicly traded
firms
- Moreover, options market behaves badly for “hot shares”
- Put-call parity is violated by large amounts of short interest